Indexing Uncertain Categorical Data over Distributed Environment
Adel Benaissa, Salima Benbernou, Mourad Ouziri, Soror Sahri
Available Online June 2015.
- https://doi.org/10.2991/ifsa-eusflat-15.2015.197How to use a DOI?
- Uncertain database, indexating, distributed environment, top-k query, query optimization, threshold query.
- Today, a large amount of uncertain data is produced by several applications where the management systems of traditional databases incuding indexing methods are not suitable to handle such type of data. In this paper, we propose an inverted based index method for effciently searching uncertain categorical data over distributed environments. We adress two kinds of query over the distributed uncertain databases, one a distributed probabilistic thresholds query, where all results sastisfying the query with probablities that meet a probablistic threshold requirement are returned, and another a distributed top k-queries, where all results optimizing the transfer of the tuples and the time reatment are returned.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Adel Benaissa AU - Salima Benbernou AU - Mourad Ouziri AU - Soror Sahri PY - 2015/06 DA - 2015/06 TI - Indexing Uncertain Categorical Data over Distributed Environment BT - Proceedings of the 2015 Conference of the International Fuzzy Systems Association and the European Society for Fuzzy Logic and Technology PB - Atlantis Press SP - 1395 EP - 1400 SN - 1951-6851 UR - https://doi.org/10.2991/ifsa-eusflat-15.2015.197 DO - https://doi.org/10.2991/ifsa-eusflat-15.2015.197 ID - Benaissa2015/06 ER -